Job description
Matterport is leading the digital transformation of the built world. Our groundbreaking spatial computing platform turns buildings into data making every space more valuable and accessible. Millions of buildings in more than 150 countries have been transformed into immersive Matterport digital twins to improve every part of the building lifecycle from planning, construction, and operations to documentation, appraisal and marketing.
We're excited to announce that Matterport will be publicly listed on NASDAQ this year. It's an exciting time to join us!
As a member of the computer vision team, you’ll be responsible for developing robust completely-automated computer vision and machine learning algorithms to handle any real-world environment our users can throw at us, from small spaces captured with mobile devices all the way up to massive stadiums scanned with professional hardware.
We work on a broad range of technologies, including point cloud alignment, generation/texturing of 3D meshes from point clouds, 3D mesh manipulation, camera calibration, SLAM, multi-view stereo, machine learning, and semantic understanding. And we’ve collected a massive database of complex real-world data that we can use to validate our approaches.
If the combination of real data, real users, and cutting-edge research appeals to you, then we’d love to talk!
Requirements:
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5+ years of experience in machine learning, computer vision, and cloud infrastructure
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Ability to write performant, well-tested, production-ready Python code (Excellent Python skills are a must!)
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Experience developing DL pipelines which leverage cloud compute and storage to train a range of CNN architectures using TensorFlow/PyTorch and are scalable up to multi-terabyte datasets
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Experience deploying trained models to either: Cloud, addressing issues of compute autoscaling or Mobile, addressing issues of model conversion (i.e. for iOS / Android)
Nice to Haves:
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Ability to read and operationalize research-quality Python / C++ code
Optimization of training / inference:
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Improve learned performance with hyperparameter tuning frameworks
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(training) reduce time while maintaining stability / final learned performance
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(inference) reduce memory usage / increase speed e.g. via quantization / pruning
Experience with Docker/Kubernetes
At Matterport, we don’t just accept differences — we celebrate it and recognize the value it brings to our customers and employees. Matterport is proud to be an equal opportunity workplace and is an affirmative action employer. Equal opportunity and consideration are afforded to all qualified applicants and employees. We won't unlawfully discriminate on the basis of gender identity or expression, race, ethnicity, religion, national origin, age, sex, marital status, physical or mental disability, Veteran status, sexual orientation, and any other category protected by law. We also consider all qualified applicants regardless of criminal histories, consistent with legal requirements.
Matterport is committed to working with and providing reasonable accommodation to applicants with disabilities in accordance with the American Disabilities Act and local disability laws. We are committed to providing employees with a work environment free of discrimination and harassment and provides a sense of inclusion and belonging.
For information regarding how Matterport collects and uses personal information, please review our Privacy Policies.
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About this role
Apply before
May 30th, 2021
Job posted on
March 31st, 2021
Job type
Full Time
Hiring timezone
Matterport is hiring for this role in the following timezones:
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About the company
Matterport is the industry leader in 3D capture and spatial data with a mission to digitize and index the built world, and advance the way people interact with the places they inhabit and explore. Matt...We'll keep you updated when the best new remote jobs pop up.